Furthermore, this illustrates the effectiveness of both models in inferring pore radius and density solely from ultrasonic attenuation data.Echolocating mammals produce directional sound beams with high source levels to improve echo-to-noise ratios and reduce clutter. Recent studies have suggested that the differential spectral gradients of such narrow beams are exploited to facilitate target localization by pointing the beam slightly off targets to maximize the precision of angular position estimates [maximizing bearing Fisher information (FI)]. Here, we test the hypothesis that echolocating toothed whales focus their acoustic gaze askew during target detection to maximize spectral cues by investigating the acoustic gaze direction of two trained delphinids (Tursiops truncatus and Pseudorca crassidens) echolocating to detect an aluminum cylinder behind a hydrophone array in a go/no-go paradigm. The animals rarely placed their beam axis directly on the target, nor within the narrow range around the off-axis angle that maximizes FI. However, the target was, for each trial, ensonified within the swath of the half-power beam width, and hence we conclude that the animals solved the detection task using a strategy that seeks to render high echo-to-noise ratios rather than maximizing bearing FI. We posit that biosonar beam adjustment and acoustic gaze strategies are likely task-dependent and that maximizing bearing FI by pointing off-axis does not improve target detection performance.For the acoustic characterization of materials, a method is proposed for interpreting experiments with finite-sized transducers and test samples in terms of the idealized situation in which plane waves are transmitted through an infinite plane-parallel layer. The method uses acoustic holography, which experimentally provides complete knowledge of the wave field by recording pressure waveforms at points on a surface intersected by the acoustic beam. The measured hologram makes it possible to calculate the angular spectrum of the beam to decompose the field into a superposition of plane waves propagating in different directions. Because these waves cancel one another outside the beam, the idealized geometry of an infinite layer can be represented by a sample of finite size if its lateral dimensions exceed the width of the acoustic beam. The proposed method relies on holograms that represent the acoustic beam with and without the test sample in the transmission path. The method is described theoretically, and its capabilities are demonstrated experimentally for silicone rubber samples by measuring their frequency-dependent phase velocities and absorption coefficients in the megahertz frequency range.Multisource localization using time difference of arrival (TDOA) is challenging because the correct combination of TDOA estimates across different microphone pairs, corresponding to the same source, is usually unknown, which is termed as the data association problem. Moreover, many existing multisource localization techniques are originally demonstrated in two dimensions, and their extensions to three dimensions (3D) are not straightforward and would lead to much higher computational complexity. In this paper, we propose an efficient, feature-based approach to tackle the data association problem and achieve multisource localization in 3D in a distributed microphone array. The features are generated by using interchannel phase difference (IPD) information, which indicates the number of times each frequency bin across all time frames has been assigned to sources. Based on such features, the data association problem is addressed by correlating most similar features across different microphone pairs, which is executed by solving a two-dimensional assignment problem successively. Thereafter, the locations of multiple sources can be obtained by imposing a single-source location estimator on the resulting TDOA combinations. The proposed approach is evaluated using both simulated data and real-world recordings.Calculus of variations is used to determine a profile shape for an acoustic black hole without a layer of viscoelastic dampening material with fixed parameters of geometry (i.e., length, maximal and minimal thickness), which minimizes the reflection coefficient, without violating the underlying assumptions of existence for acoustic black holes. The additional constraint imposed by keeping the normalized wave number variation (NWV) small everywhere in the acoustic black hole is handled by the use of Lagrange multipliers. From this method, closed-form expressions for the optimal profile, its reflection coefficient, and the NWV are derived. Additionally, it is shown that in the special case where only the NWV (and not the reflection coefficient) is considered, the optimal profile reduces to the well-known thickness profile for acoustic black holes, h(x)=?x2. We give a numerical example of the difference between an acoustic black hole with optimal profile and classical profile, h(x)=?xm, m &gt; 2. https://www.selleckchem.com/products/raptinal.html For close to identical reflection coefficients, the optimal profile vastly outperforms the classical profile in terms of having low NWV at a large range of frequencies.Critical acoustical systems operating in complex environments contaminated with disturbances and noise offer an extreme challenge when excited by out-of-the-ordinary, impulsive, transient events that can be undetected and seriously affect their overall performance. Transient impulse excitations must be detected, extracted, and evaluated to determine any potential system damage that could have been imposed; therefore, the problem of recovering the excitation in an uncertain measurement environment becomes one of multichannel deconvolution. Recovering a transient and its initial energy has not been solved satisfactorily, especially when the measurement has been truncated and only a small segment of response data is available. The development of multichannel deconvolution techniques for both complete and incomplete excitation data is discussed, employing a model-based approach based on the state-space representation of an identified acoustical system coupled to a forward modeling solution and a Kalman-type processor for enhancement and extraction.